Improving adoptability of farm forestry in the Philippine uplands: a linear programming model

In the Philippines, smallholder farmers have become major timber producers. But the systems of timber production practiced have several limitations. In intercropping systems, the practice of severe branch and/or root pruning reduces tree-crop competition and increases annual crop yields, but is detrimental to tree growth and incompatible with commercial timber production. In even-aged woodlots, lack of regular income and poor tree growth, resulting from farmers’ reluctance to thin their plantations, are major constraints to adoption and profitable tree farming. In the municipality of Claveria, Misamis Oriental, the recent practice of planting trees on widely spaced (6–8 m) contour grass strips established for soil conservation suggests ways to improve the adoptability (i.e., profitability, feasibility and acceptability) of timber-based agroforestry systems. Assuming that financial benefits are the main objective of timber tree farmers, we develop a simple linear programming (LP) model for the optimal allocation of land to monocropping and tree intercropping that maximizes the net present value of an infinite number of rotations and satisfies farmers’ resource constraints and regular income requirements. The application of the LP model to an average farmer in Claveria showed that cumulative additions of widely spaced tree hedgerows provides higher returns to land, and reduce the risk of agroforestry adoption by spreading over the years labour and capital investment costs and the economic benefits accruing to farmers from trees. Therefore, incremental planting of widely spaced tree hedgerows can make farm forestry more adoptable and thus benefit a larger number of resource-constrained farmers in their evolution towards more diverse and productive agroforestry systems.     

A Danish example of optimal thinning strategies in mixed-species forest under changing growth conditions caused by climate change

In this study, we analyse the economic and managerial aspects of option values related to having a mixed-species stand. As an example, we look at a mixed Norway spruce and Sitka spruce stand in Denmark when timing and intensity of future climate, and its effect on tree growth, are uncertain. Assuming that tree growth follows a discrete non-stationary stochastic process, we use dynamic programming to optimise the harvest distribution between the two species.

The results show that facing growth uncertainty caused by potential climate change implies an option value. Such uncertainty can be a potential advantage as long as we are able to maintain flexibility, keep decisions open, and there is a chance that climatic change will benefit some species. We analyse the model under different uncertainty assumptions and show that the larger changes we expect, the higher is the option value at any time during the stand’s life and, hence, we keep, on average, both tree species in the stand for a longer period of time. Moreover, we find that the adjustments may take place rather late in the rotation, a result brought about by the significance of the option value, which makes it optimal to maintain a reasonable stocking of both species.     

Conversion to organic arable farming in The Netherlands: A dynamic linear programming analysis

Several studies show that organic farming is more profitable than conventional farming. However, in reality not many farmers convert to organic farming. Policy makers and farmers do not have clear insight into factors which hamper or stimulate the conversion to organic farming. The objective of this paper is to develop a dynamic linear programming model to analyse the effects of different limiting factors on the conversion process of farms over time. The model is developed for a typical arable farm in The Netherlands central clay region, and is based on two static liner programming models (conventional and organic). The objective of the model is to maximise the net present value over a 10-year planning horizon. The results of the analysis of a basic scenario show that conversion to organic farming is more profitable than staying conventional. In order to arrive at the actual profitable phase of organic farming, the farmer has to pass through the economically difficult 2-year conversion period. Sensitivity analysis shows that if depreciation is 25% higher than conventional fixed costs due to machinery made superfluous by conversion, conversion is less profitable than staying conventional. Also the availability of hired labour, which can be constrained in peak periods, has a strong effect on the cropping plan and the amount of area converted. Further analysis shows that a slight drop (2%) in organic prices lowers the labour income of the farmer and makes conversion less profitable than conventional farming. For farmers, a minimum labour income can be required to ‘survive’. The analysis shows that constraint on minimum labour income makes stepwise conversion the best way for farmers to overcome economic difficulties during conversion.     

基于AutoCAD2000的二维图形自动编程软件的开发

介绍了基于AUTOCAD2000、采用Visual LISP作为开发工具的二维图形自动编程系统的开发，并详细介绍了数据结构、实体排序技术及各模块之间数据流的传送．并通过实例讲解了软件的应用。     

锦屏拱坝基础变形模量多目标非线

基础变形模量对坝体的安全运行和受力有着十分重要的意义，特别是高拱坝，需要良好的基础变形模量，但是在一定的荷载运行工况下，并不是意味着基础变形模量越高坝体应力、稳定、变形状况就越好。基于上述观点，利用多目标非线性规划方法对锦屏拱坝最优基础变形模量进行了研究，给出了拱坝在最优基础变形模量条件下坝体应力、稳定、变形及基础处理费用等特征值。研究表明：经过基础变形模量的优化，能有效改善坝体应力、位移、稳定等多项指标。     

Resource allocation tradeoffs in Manila’s peri-urban vegetable production systems: An application of multiple objective programming

This paper designed and developed a multi-objective programming (MOP) model to illustrate the dynamic relationship among technologies, productive activities, constraints and farmers’ objectives in the peri-urban vegetable production system and use the model as an economic tool in analysing probable consequences of a given action or innovation on the farm. The best compromise solution was generated using four analytical steps, as follows: single-objective optimization (to determine the ideal and anti-ideal values of the objective functions); constrained optimization (to generate the set of Pareto non-dominated solutions); cluster analysis (to trim down efficient set into smaller homogeneous groups); and compromise programming (to determine where the best compromise solution lies).     

基于CMAC神经网络的自适应渠道输水自动控制研究

介绍了小脑模型神经网络CMAC的原理及基于CMAC的自动控制方法。在渠道输水控制技术的基础上,依据CMAC神经网络学习速度快、能够表达复杂非线性关系、适合于适时控制的特点,提出了基于CMAC的渠道输水控制模型。仿真结果表明,基于CMAC的渠道输水控制,算法简单方便,具有实时性、稳定性和较强的鲁棒性,控制效果较为理想。     

并联泵站群日优化运行方案算法

提出了并联泵站群日优化运行数学模型,该模型以并联泵站群日提水费用最少为目标函数,以各时段机组叶片角或转速为决策变量.考虑站间不同工况调节方式,采用大系统二级分解-动态规划聚合法进行求解.首先以泵站日提水耗电费用最少为目标,泵站提水量的分配为协调变量,将该模型分解成若干个泵站多机组日优化运行一级子模型;再以单机组日提水耗电费用最少为目标,机组提水量的分配为协调变量,将一级子模型分解为若干个单机组日优化运行二级子模型.该二级子模型以机组叶片安放角或机组转速为决策变量,机组提水量的离散值为状态变量,采用动态规划方法求解.构造的聚合模型以各机组提水量为决策变量,并联泵站群提水量的离散值为状态变量,同样采用动态规划方法求解.该方法可以解决不同工况调节方式、不同时段划分及不同日均扬程下并联泵站群的日优化运行问题.以淮阴一、三站并联运行为例,作了日优化运行计算,结果表明：各日均扬程下满负荷、80%负荷、60%负荷优化运行单位费用,较定角恒速运行分别平均节约10.53%,26.54%,34.40%.     

灌溉兼防洪水库的优化调度

我国干旱半干旱地区，天然降水量少且时程及地域相差大，并有很大的随机性。对有水库调节的地区，如何处理天然降水的随机性，合理利用有限的水资源，解决人畜饮水、工业用水、林业及农业灌溉耗水，使其在各种情况下都能达到最佳的社会效益和经济效益，该文选用动态规划法，编制的电算程序，很好地解决了这一问题。     

基于DPSA算法的“单库-单站”水资源优化调度方法研究

提出了单座水库与单座补水泵站水资源优化调度的非线性数学模型,模型以年内各时段的缺(弃)水量的平方最小为目标函数,各时段水库供水量和泵站引提水量为决策变量,各时段水库库容为状态变量,以年调节水库可供水量、泵站年引提水总量、水库与补水泵站的联合运行准则(泵站闲时补库、忙时供水)等为约束条件,并以南水北调东线一期江苏境内"骆马湖-皂河站"为实例,采用动态规划逐次逼近法进行求解。结果表明,相同供水保证率时,50%、75%、95%来水频率下泵站补水量、缺水量、弃水量比常规调度均有减少。